In the current business environment, industries and enterprises are continuously looking for means and models to operate efficiently and to meet ever evolving customer demands. Digitization of various processes and activities in an industry or an enterprise is one such means that is being enabled by the advancements in the field of Information Technology (IT). This digitization is deployed using IT infrastructures that involve a complex combination of devices and software solutions. However, to derive the benefits of digitization, the IT infrastructures need to run smoothly.
Various tools have been designed and developed to monitor and/or predict any anomaly or malfunctioning in these IT infrastructures so that the anomaly can be resolved quickly and proactively. However, despite much advancement the resolutions provided by the support team are at times delayed and/or not accurate. Such delays accrue due to many reasons, among which few being the sheer load of unwanted and/or redundant alerts or tickets corresponding to various anomalies or defects in IT infrastructures that get logged requiring attention of the support team to resolve them quickly. Various existing optimization tools and techniques to address this concern still don't address the problem effectively. Hence, the technical support teams face the barrage of unwanted alerts or tickets to resolve and thereby limiting the time that is required to address the genuine and the critical alerts or tickets. These limitations, in turn, affect the overall functioning of the organization or the enterprise. Automation is one of way to resolve the alerts or tickets without human intervention so as to increase resolution efficiency and to reduce cost. However, identification of automation candidate among tickets and invoking corresponding resolution script still requires some manual efforts.